Identification of Key Genes for Pyroptosis-Induced Salivary Gland Inflammation in Sjogren's Syndrome Based on Microarray Data and Immunohistochemistry Analysis

基于微阵列数据和免疫组织化学分析鉴定干燥综合征中细胞焦亡诱导的唾液腺炎症的关键基因

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作者:Kaiyuan Zhang #, Ziyue Luo #, Xinchao Zhu, Xinyi Yao, Dingqi Lu, Liying Chen, Tao Hong, Yating Ren, Xinchang Wang

Conclusion

Our study revealed enhanced levels of pyroptosis in the SS. GZMA and GBP1 were identified as candidate genes for pyroptosis-induced inflammation of the SG in SS, which may be used as biomarkers or potential therapeutic targets for SS.

Methods

GSE157159 dataset and GSE159574 dataset were downloaded from Gene Expression Omnibus (GEO). Differentially Expressed Genes (DEGs) analysis was used to screen DEGs from SS and non-SS SG samples. Pyroptosis-related genes were obtained from GeneCards. After intersecting DEGs with pyroptosis-related genes, the pyroptosis-related DEGs in SS were obtained. Subsequently, ClueGO enrichment analysis, Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analysis, Protein-protein Interaction (PPI), and identification and co-expression analysis of hub genes were performed. Subsequently, we collected SG samples from 17 SS patients and 17 non-SS patients and validated the expression of two hub genes (GZMA, GBP1) and characteristic genes (GSDMD) of pyroptosis through immunohistochemistry. The accuracy of hub genes as biomarkers for predicting SS was evaluated by receiver operating characteristic (ROC) curve.

Purpose

Sjogren's Syndrome (SS) is a systemic autoimmune disease primarily characterized by dysfunction of the exocrine glands. Research into the etiology and pathogenesis of salivary glands (SG) inflammation of SS is very limited. The aim of this study was to identify potential pyroptosis-related genes in SG inflammation through bioinformatics analysis and validation of the SG in SS.

Results

834 DEGs were selected from the GSE157159 dataset, and a total of 39 pyroptosis-related DEGs were obtained. Functional analysis showed that these DEGs were significantly enriched in some inflammatory signaling pathways. Through the intersection of seven algorithms proposed by CytoHubba and validation using the GSE159574 dataset, 11 hub genes were identified, including IL18, AIM2, CCL5, CD274, GBP1, GBP5, GZMA, GZMB, TLR8, TNFS13B, and ICAM1. Finally, the results of immunohistochemistry showed that GSDMD, GZMA and GBP1 were all significantly highly expressed in SG from SS. And ROC analysis showed a high combined diagnostic value of the 3 genes (AUC=0.8858).

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